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Engineering Manager, Data Knowledge Platform Engineering

SpringCube

Full time - Engineering Manager

Fintech

United States, San Francisco - California

Published 6 days ago

Salary: Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A global fintech and payments platform empowers businesses worldwide with unified financial solutions. The company supports over 200,000 businesses—including leading global brands—with end-to-end tools for business accounts, payments, spend management, treasury, and embedded finance. Founded in Melbourne, the organization has 2,000+ tech professionals across 26 offices and is valued at US$8 billion. Backed by top-tier investors such as T. Rowe Price, Visa, Mastercard, Sequoia, and Salesforce Ventures, it is focused on building the next-generation global payments and financial platform.

About the Role
The Engineering Manager for the Data Knowledge Platform will lead cross-functional initiatives across the company’s data ecosystem. This role involves defining a multi-year technical roadmap, scaling engineering teams, and ensuring the data platform can support AI and real-time analytics at enterprise scale. The role requires strong leadership, deep technical expertise, and the ability to drive high-impact data solutions across the organization.

Responsibilities

  • Provide visionary technical leadership and define a clear 1-3 year strategic roadmap for the Realtime Data Platform
  • Lead modernization of the core data platform, enabling real-time analytical processing at petabyte scale
  • Partner with product teams to enable AI-powered applications, real-time dashboards, and other data-driven features
  • Scale and structure engineering teams, including hiring, mentoring, and developing managers and senior contributors
  • Cultivate strong relationships with product and engineering teams, acting as a trusted technical advisor on Data and AI initiatives
  • Drive architecture design decisions and evaluate emerging technologies to enhance platform capabilities

Qualifications

  • Minimum 8 years of experience in data or software engineering, with at least 3 years in a leadership role
  • Proven experience managing and scaling engineering teams of 10+ people, including managers and senior contributors
  • Strong ability to define and execute technical strategies resulting in measurable business outcomes
  • Deep expertise in distributed data processing (e.g., Apache Spark, Databricks) and event streaming (e.g., Kafka)
  • Knowledge of modern data storage and serving technologies such as CubeJS, ElasticSearch, Clickhouse
  • Familiarity with observability tools such as Splunk, Grafana, and Prometheus
  • Preferred: Experience in the financial domain, hands-on design for modern Lakehouse architectures, excellent communication skills for diverse audiences, ability to rapidly evaluate technologies and conduct proofs of concept

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.